Amazon cover image
Image from Amazon.com
Image from Google Jackets
Image from OpenLibrary

The 'R' Book

By: Material type: TextTextPublication details: Chichester, West Sussex, United Kingdom Wiley 2013Edition: 2nd edDescription: xxiv, 1051 pages : illustrations (come color) ; 26 cmISBN:
  • 9780470973929
Subject(s): DDC classification:
  • 519.502855133 CRA-R
Contents:
Preface -- 1. Getting Started -- 2. Essentials of the R Language -- 3. Data Input -- 4. Dataframes -- 5. Graphics -- 6 Tables -- 7. Mathematics -- 8. Classical Tests -- 9. Statistical Modelling -- 10. Regression -- 11. Analysis of Variance -- 12. Analysis of Covariance -- 13. Generalized Linear Models -- 14. Count Data -- 15. Count Data in Tables -- 16. Proportion Data -- 17. Binary Response Variables -- 18. Generalized Additive Models -- 19. Mixed-Effects Models -- 20. Non-linear Regression -- 21. Meta-analysis -- 22. Bayesian statistics -- 23. Tree Models -- 24. Time Series Analysis -- 25. Multivariate Statistics -- 26. Spatial Statistics -- 27. Survival Analysis -- 28. Simulation Models -- 29. Changing the Look of Graphics.
Summary: "Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Computational Biology and Bioinformatics Processing Center Dept. of Computational Biology and Bioinformatics 519.502855133 CRA-R (Browse shelf(Opens below)) Available DCB2782

Preface -- 1. Getting Started -- 2. Essentials of the R Language -- 3. Data Input -- 4. Dataframes -- 5. Graphics -- 6 Tables -- 7. Mathematics -- 8. Classical Tests -- 9. Statistical Modelling -- 10. Regression -- 11. Analysis of Variance -- 12. Analysis of Covariance -- 13. Generalized Linear Models -- 14. Count Data -- 15. Count Data in Tables -- 16. Proportion Data -- 17. Binary Response Variables -- 18. Generalized Additive Models -- 19. Mixed-Effects Models -- 20. Non-linear Regression -- 21. Meta-analysis -- 22. Bayesian statistics -- 23. Tree Models -- 24. Time Series Analysis -- 25. Multivariate Statistics -- 26. Spatial Statistics -- 27. Survival Analysis -- 28. Simulation Models -- 29. Changing the Look of Graphics.

"Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

There are no comments on this title.

to post a comment.